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<Paper uid="C04-1057">
  <Title>A Formal Model for Information Selection in Multi-Sentence Text Extraction</Title>
  <Section position="7" start_page="0" end_page="0" type="concl">
    <SectionTitle>
6 Conclusion
</SectionTitle>
    <Paragraph position="0"> In this paper we proposed a formal model for information selection and redundancy avoidance in summarization and question-answering. Within this two-dimensional model, summarization and question-answering entail mapping textual units onto conceptual units, and optimizing the selection of a subset of textual units that maximizes the information content of the covered conceptual units.</Paragraph>
    <Paragraph position="1"> The formalization of the process allows us to benefit from theoretical results, including suitable approximation algorithms. Experiments using DUC data showed that this approach does indeed lead to improvements due to better information packing over a straightforward content selection method.</Paragraph>
  </Section>
class="xml-element"></Paper>